PaperBLAST: Text Mining Papers for Information about Homologs

ABSTRACT Large-scale genome sequencing has identified millions of protein-coding genes whose function is unknown. Many of these proteins are similar to characterized proteins from other organisms, but much of this information is missing from annotation databases and is hidden in the scientific liter...

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Autores principales:	Morgan N. Price, Adam P. Arkin
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2017
Materias:	annotation text mining Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/9ba677cd6ce54424bb3541f7d99afce9
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spelling	oai:doaj.org-article:9ba677cd6ce54424bb3541f7d99afce92021-12-02T18:39:33ZPaperBLAST: Text Mining Papers for Information about Homologs10.1128/mSystems.00039-172379-5077https://doaj.org/article/9ba677cd6ce54424bb3541f7d99afce92017-08-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSystems.00039-17https://doaj.org/toc/2379-5077ABSTRACT Large-scale genome sequencing has identified millions of protein-coding genes whose function is unknown. Many of these proteins are similar to characterized proteins from other organisms, but much of this information is missing from annotation databases and is hidden in the scientific literature. To make this information accessible, PaperBLAST uses EuropePMC to search the full text of scientific articles for references to genes. PaperBLAST also takes advantage of curated resources (Swiss-Prot, GeneRIF, and EcoCyc) that link protein sequences to scientific articles. PaperBLAST’s database includes over 700,000 scientific articles that mention over 400,000 different proteins. Given a protein of interest, PaperBLAST quickly finds similar proteins that are discussed in the literature and presents snippets of text from relevant articles or from the curators. PaperBLAST is available at http://papers.genomics.lbl.gov/ . IMPORTANCE With the recent explosion of genome sequencing data, there are now millions of uncharacterized proteins. If a scientist becomes interested in one of these proteins, it can be very difficult to find information as to its likely function. Often a protein whose sequence is similar, and which is likely to have a similar function, has been studied already, but this information is not available in any database. To help find articles about similar proteins, PaperBLAST searches the full text of scientific articles for protein identifiers or gene identifiers, and it links these articles to protein sequences. Then, given a protein of interest, it can quickly find similar proteins in its database by using standard software (BLAST), and it can show snippets of text from relevant papers. We hope that PaperBLAST will make it easier for biologists to predict proteins’ functions.Morgan N. PriceAdam P. ArkinAmerican Society for Microbiologyarticleannotationtext miningMicrobiologyQR1-502ENmSystems, Vol 2, Iss 4 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	annotation text mining Microbiology QR1-502
spellingShingle	annotation text mining Microbiology QR1-502 Morgan N. Price Adam P. Arkin PaperBLAST: Text Mining Papers for Information about Homologs
description	ABSTRACT Large-scale genome sequencing has identified millions of protein-coding genes whose function is unknown. Many of these proteins are similar to characterized proteins from other organisms, but much of this information is missing from annotation databases and is hidden in the scientific literature. To make this information accessible, PaperBLAST uses EuropePMC to search the full text of scientific articles for references to genes. PaperBLAST also takes advantage of curated resources (Swiss-Prot, GeneRIF, and EcoCyc) that link protein sequences to scientific articles. PaperBLAST’s database includes over 700,000 scientific articles that mention over 400,000 different proteins. Given a protein of interest, PaperBLAST quickly finds similar proteins that are discussed in the literature and presents snippets of text from relevant articles or from the curators. PaperBLAST is available at http://papers.genomics.lbl.gov/ . IMPORTANCE With the recent explosion of genome sequencing data, there are now millions of uncharacterized proteins. If a scientist becomes interested in one of these proteins, it can be very difficult to find information as to its likely function. Often a protein whose sequence is similar, and which is likely to have a similar function, has been studied already, but this information is not available in any database. To help find articles about similar proteins, PaperBLAST searches the full text of scientific articles for protein identifiers or gene identifiers, and it links these articles to protein sequences. Then, given a protein of interest, it can quickly find similar proteins in its database by using standard software (BLAST), and it can show snippets of text from relevant papers. We hope that PaperBLAST will make it easier for biologists to predict proteins’ functions.
format	article
author	Morgan N. Price Adam P. Arkin
author_facet	Morgan N. Price Adam P. Arkin
author_sort	Morgan N. Price
title	PaperBLAST: Text Mining Papers for Information about Homologs
title_short	PaperBLAST: Text Mining Papers for Information about Homologs
title_full	PaperBLAST: Text Mining Papers for Information about Homologs
title_fullStr	PaperBLAST: Text Mining Papers for Information about Homologs
title_full_unstemmed	PaperBLAST: Text Mining Papers for Information about Homologs
title_sort	paperblast: text mining papers for information about homologs
publisher	American Society for Microbiology
publishDate	2017
url	https://doaj.org/article/9ba677cd6ce54424bb3541f7d99afce9
work_keys_str_mv	AT morgannprice paperblasttextminingpapersforinformationabouthomologs AT adamparkin paperblasttextminingpapersforinformationabouthomologs
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PaperBLAST: Text Mining Papers for Information about Homologs

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